Bioleaching of Indonesian Galena Concentrate With an Iron- and Sulfur-Oxidizing Mixotrophic Bacterium at Room Temperature
Bibliographic record
Abstract
Biohydrometallurgy is believed to be a promising future study field for the recovery of lead (Pb) from ores/concentrates since the pyrometallurgical/hydrometallurgical processes have been largely applied to recover Pb to date, which operates at high temperature and generates volatile Pb matters that are hazardous and carcinogenic to human health. Hence, the main purpose of this study was to investigate the biohydrometallurgical extraction of Pb from the Indonesian galena concentrate through bioleaching using an iron- and sulfur-oxidizing mixotrophic bacterium (identified as Citrobacter sp.). The bioleaching experiments were conducted in shake flasks containing the modified LB broth medium supplemented with galena concentrate with a particle size of d80 = 75 μm at room temperature. Both semi-direct and direct bioleaching methods were employed in this study. The bacterium was able to extract lead (Pb) from galena concentrate with high selectivity to Cu and Zn (0.99 and 0.86, respectively). The highest extraction level of 90 g lead dissolved/kg galena concentrate was achieved using direct bioleaching method at bioleaching conditions of 2% w/v pulp density, 5 g/L FeCl3, 50 g/L NaCl, 20 g/L molasses and a rotation speed of 180 rpm at room temperature (25 oC). The addition of FeCl3, NaCl, and molasses increased the lead leaching efficiencies, which were also evidenced by the FTIR, XRD, and SEM-EDS analyses. From industrial and commercial standpoints, the selective bioleaching represented in this study may be beneficial to the development of lead leaching from sulfide minerals, since insoluble anglesite (PbSO4) precipitates are formed during ferric sulfate oxidation, thus making the recovery of lead through bioleaching unpractical.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".